Parameterized Models for Facial Animation

Parke, S.

doi:10.1109/mcg.1982.1674492

Cited by 393 publications

(153 citation statements)

References 7 publications

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“…The talking head used in the studies is detailed in [11] and includes a face, eyes, tongue, and teeth, based on static 3D-wireframe meshes that are deformed using direct parameterizations by applying weighted transformations to their vertices according to principles first introduced by [12]. Figure 2 shows the 3D projection surface with and without a projection of the talking head.…”

Section: Projected Animated Faces On 3d Head Modelsmentioning

confidence: 99%

Animated Faces for Robotic Heads: Gaze and Beyond

Moubayed

Beskow

Edlund

et al. 2011

Lecture Notes in Computer Science

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Abstract. We introduce an approach to using animated faces for robotics where a static physical object is used as a projection surface for an animation. The talking head is projected onto a 3D physical head model. In this chapter we discuss the different benefits this approach adds over mechanical heads. After that, we investigate a phenomenon commonly referred to as the Mona Lisa gaze effect. This effect results from the use of 2D surfaces to display 3D images and causes the gaze of a portrait to seemingly follow the observer no matter where it is viewed from. The experiment investigates the perception of gaze direction by observers. The analysis shows that the 3D model eliminates the effect, and provides an accurate perception of gaze direction. We discuss at the end the different requirements of gaze in interactive systems, and explore the different settings these findings give access to.

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Section: Projected Animated Faces On 3d Head Modelsmentioning

confidence: 99%

Animated Faces for Robotic Heads: Gaze and Beyond

Moubayed

Beskow

Edlund

et al. 2011

Lecture Notes in Computer Science

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“…Parametric face models [8][9][10][11] and many commercial modelers fall into this approach. The desire is to create an encapsulated model that can generate a wide range of faces based on a small set of input parameters.…”

Section: Background and Previous Workmentioning

confidence: 99%

Face to Face: Anthropometry‐Based Interactive Face Shape Modeling Using Model Priors

Prakash

2009

International Journal of Computer Games Technology

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This paper presents a new anthropometrics-based method for generating realistic, controllable face models. Our method establishes an intuitive and efficient interface to facilitate procedures for interactive 3D face modeling and editing. It takes 3D face scans as examples in order to exploit the variations presented in the real faces of individuals. The system automatically learns a model prior from the data-sets of example meshes of facial features using principal component analysis (PCA) and uses it to regulate the naturalness of synthesized faces. For each facial feature, we compute a set of anthropometric measurements to parameterize the example meshes into a measurement space. Using PCA coefficients as a compact shape representation, we formulate the face modeling problem in a scattered data interpolation framework which takes the user-specified anthropometric parameters as input. Solving the interpolation problem in a reduced subspace allows us to generate a natural face shape that satisfies the user-specified constraints. At runtime, the new face shape can be generated at an interactive rate. We demonstrate the utility of our method by presenting several applications, including analysis of facial features of subjects in different race groups, facial feature transfer, and adapting face models to a particular population group.

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“…The set of parameters from Parke's model [49] distinguished conformation parameters from expression parameters. This set was then extended by adding speech parameters to include lip synchronization [30,51,48,12].…”

Section: Introductionmentioning

confidence: 99%

Synthesizing cooperative conversation

Pélachaud

Cassell

Badler

et al. 1998

Multimodal Human-Computer Communication

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We describe an implemented system which automatically generates and animates conversations between multiple human-like agents with appropriate and synchronized speech, intonation, facial expressions, and hand gestures. Conversations are created by a dialogue planner that produces the text as well as the intonation of the utterances. The speaker/listener relationship, the text, and the intonation in turn drive facial expressions, lip motions, eye gaze, head motion, and arm gesture generators. Disciplines AbstractWe describe an implemented system which automatically generates and animates conversations between multiple human-like agents with appropriate and synchronized speech, intonation, facial expressions, and hand gestures. Conversations are created by a dialogue planner that produces the text as well as the intonation of the utterances. The speaker/listener relationship, the text, and the intonation in turn drive facial expressions, lip motions, eye gaze, head motion, and arm gesture generators.

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Parameterized Models for Facial Animation

Cited by 393 publications

References 7 publications

Animated Faces for Robotic Heads: Gaze and Beyond

Animated Faces for Robotic Heads: Gaze and Beyond

Face to Face: Anthropometry‐Based Interactive Face Shape Modeling Using Model Priors

Synthesizing cooperative conversation

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